ttempts at improving diversity, equity, and inclusion (DEI) access across US healthcare is a much-welcomed, if not long-overdue, development in recent years. Substantive DEI legislation was signed into US law in December 2022 (and went into effect in February 2023), helping to correct significant disparities (explained below) and holding sponsors responsible for ensuring that their trials include participants from diverse groups. As we learned from vaccine development during the pandemic, clinical trials must address diverse participant populations to determine the real-world impacts on safety and efficacy for novel therapies. Data analytics tools can help.
While this information is not surprising, it should nonetheless be cause for alarm. Beyond the obvious notions of ensuring fairness and respect for all individuals regardless of their race, gender, sexual orientation, age, religion, ability, or any other personal characteristic, these efforts will drive many additional benefits such as reducing outcome bias, which may increase the risk of adverse events and the approval of therapies that are ineffective in marginalized populations. For example, one top reason for FDA drug recalls is adverse events in women.
No one doubts the inherent value of broader representation in clinical trials. However, pharmaceutical sponsors are uncertain of what these new regulations mean for upcoming clinical trials. One concern, according to various conversations with research professionals, is that such regulation might impact their ability to carry out any research at all.
“Everyone realizes the benefits of representative populations as participants in clinical trials,” said one multinational pharmaceutical company clinical operations executive in an April 2023 interview. “Now the issue has more to do with how granular regulations might get, how it fits into overall drug development strategies, and whether it might ultimately hinder our ability to address the requirements across all regions of development while controlling for costs and ensuring scientific rigor.”
Sponsors will need a reliable mechanism to ensure the representation of diverse participants in their trials, or risk potentially negative consequences. For example, one organization faced slowdowns during its COVID-19 vaccine trials due to a failure to recruit enough minority participants. With this new regulation in place, the risks are bigger and impact even more consequential.
Preventing Trial Derailment with Data Analytics
One way to mitigate potential impacts is with systematic data analytics. Sponsors and contract research organizations (CROs) will need to manage ever-growing volumes of data in real time to ensure that trials meet planned timelines while addressing DEI goals aligned with diversity plans submitted to FDA. Yet managing such data is difficult, particularly given the rapidly growing number of trial data points.
According to a 2021 study by Tufts University, phase 3 clinical trials generated an average of 3.6 million data points, three times the amount of data collected by late-stage trials in 2011. Calculations by one information technology firm that uses analytics and visualization to manage analysis suggest that these clinical trial data sets will skyrocket to seven multiples of 2011 by 2030.
Today’s avalanche of data is both a blessing and a curse. Data are only useful if they can be analyzed effectively, and increasing novel data types and volumes exacerbates the challenge. The new DEI requirements will make data analysis even more important—and, especially for small- to midsize biopharmaceutical companies, more onerous.
Fortunately, advanced data analytics can shift the paradigm in clinical trial operations. Technology that centralizes all data sources to power machine learning models that anticipate clinical trial events (and their impact on trial execution) empowers sponsors to mitigate challenges before it is too late. Such technology reduces friction with outsourced vendors, improves data transparency, and unifies complex interactions across stakeholders (including patients, sites, sponsors, and CROs) to ensure that each stakeholder has the right information at the right time, optimizing trial conduct.
“Smart companies are starting to leverage advanced technology and data analytics to better predict the progress of trials,” added the same clinical research professional. “There’s a huge advantage in being able to leverage robust statistical monitoring to see trends in data and be able to identify trials that might be going off track before it is too late. Ultimately, that will save sponsors a lot of time and money—particularly with DEI initiatives.”
Diversity challenges are the next frontier for advanced analytics in clinical trials. Sponsors historically contract with the same, familiar sites, so the pool of patient data is, likewise, homogenous. Data-driven technology gives sponsors and vendors complete, continuous visibility into the progress of planned DEI initiatives. Specifically, data-agnostic predictive platforms generate important insights—such as identifying sites with diverse and indication-specific patient populations (or those without those diverse populations, so sponsors and CROs can take appropriate remedial actions, such as implementing a decentralized option with remote capabilities to supplement the in-clinic needs)—across a wider set of data sources that have been utilized. A system that leverages various data sources, on the other hand, provides insights that maximize diverse recruitment and minimize bias at the outset of a clinical trial.
In addition, real-time analytics can provide rapid feedback to sites on the diversity of their randomized participants. This empowers sites, which have typically been disenfranchised from study conduct analytics, to make timely adjustments, optimizing recruitment plans in-line with diversity requirements.
Since the new US diversity plan requirements just recently became law at the end of February 2023, many of these considerations are based on a future state use case. Even so, this same predictive intelligence has already helped sponsors and CROs identify various issues before milestone dates using a proprietary data asset of over 2,000 trials. Delivering real-time, predictive analytics modeled from a data-agnostic data set has resulted in a 70x improvement in enrollment forecast accuracy, over $1 million in cost savings from patient retention, and six months’ time savings from detecting site noncompliance issues per trial.
A Call to Action for Study Sponsors
Now that the FDA is requiring adherence to diversity plans integrated into protocol designs, clinical trial sponsors have even more data to manage and absorb, and more risk. Anticipating when a trial is veering off the established plan for diversity and population representation is critical, but doing so before the end of the trial or enrollment period is paramount. If a sponsor can act quickly, they can pivot and ensure that the trial stays on track to hit all its milestones.
These new DEI requirements represent an important step forward in ensuring that clinical trials in the US reduce outcome bias while producing the valuable information that researchers need to prove that novel therapies are truly safe and efficacious. Now it is up to sponsors to do their part to address the disparities that continue to plague healthcare.